# ==================================================================== # # TITLE # # Antimicrobial Resistance (AMR) Data Analysis for R # # # # SOURCE # # https://github.com/msberends/AMR # # # # LICENCE # # (c) 2018-2021 Berends MS, Luz CF et al. # # Developed at the University of Groningen, the Netherlands, in # # collaboration with non-profit organisations Certe Medical # # Diagnostics & Advice, and University Medical Center Groningen. # # # # This R package is free software; you can freely use and distribute # # it for both personal and commercial purposes under the terms of the # # GNU General Public License version 2.0 (GNU GPL-2), as published by # # the Free Software Foundation. # # We created this package for both routine data analysis and academic # # research and it was publicly released in the hope that it will be # # useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. # # # # Visit our website for the full manual and a complete tutorial about # # how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # ==================================================================== # #' Count Available Isolates #' #' @description These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in `summarise()` from the `dplyr` package and also support grouped variables, see *Examples*. #' #' [count_resistant()] should be used to count resistant isolates, [count_susceptible()] should be used to count susceptible isolates. #' @inheritSection lifecycle Stable Lifecycle #' @param ... one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with [as.rsi()] if needed. #' @inheritParams proportion #' @inheritSection as.rsi Interpretation of R and S/I #' @details These functions are meant to count isolates. Use the [resistance()]/[susceptibility()] functions to calculate microbial resistance/susceptibility. #' #' The function [count_resistant()] is equal to the function [count_R()]. The function [count_susceptible()] is equal to the function [count_SI()]. #' #' The function [n_rsi()] is an alias of [count_all()]. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to `n_distinct()`. Their function is equal to `count_susceptible(...) + count_resistant(...)`. #' #' The function [count_df()] takes any variable from `data` that has an [`rsi`] class (created with [as.rsi()]) and counts the number of S's, I's and R's. It also supports grouped variables. The function [rsi_df()] works exactly like [count_df()], but adds the percentage of S, I and R. #' @inheritSection proportion Combination Therapy #' @seealso [`proportion_*`][proportion] to calculate microbial resistance and susceptibility. #' @return An [integer] #' @rdname count #' @name count #' @export #' @inheritSection AMR Read more on Our Website! #' @examples #' # example_isolates is a data set available in the AMR package. #' ?example_isolates #' #' count_resistant(example_isolates$AMX) # counts "R" #' count_susceptible(example_isolates$AMX) # counts "S" and "I" #' count_all(example_isolates$AMX) # counts "S", "I" and "R" #' #' # be more specific #' count_S(example_isolates$AMX) #' count_SI(example_isolates$AMX) #' count_I(example_isolates$AMX) #' count_IR(example_isolates$AMX) #' count_R(example_isolates$AMX) #' #' # Count all available isolates #' count_all(example_isolates$AMX) #' n_rsi(example_isolates$AMX) #' #' # n_rsi() is an alias of count_all(). #' # Since it counts all available isolates, you can #' # calculate back to count e.g. susceptible isolates. #' # These results are the same: #' count_susceptible(example_isolates$AMX) #' susceptibility(example_isolates$AMX) * n_rsi(example_isolates$AMX) #' #' \donttest{ #' if (require("dplyr")) { #' example_isolates %>% #' group_by(hospital_id) %>% #' summarise(R = count_R(CIP), #' I = count_I(CIP), #' S = count_S(CIP), #' n1 = count_all(CIP), # the actual total; sum of all three #' n2 = n_rsi(CIP), # same - analogous to n_distinct #' total = n()) # NOT the number of tested isolates! #' #' # Number of available isolates for a whole antibiotic class #' # (i.e., in this data set columns GEN, TOB, AMK, KAN) #' example_isolates %>% #' group_by(hospital_id) %>% #' summarise(across(aminoglycosides(), n_rsi)) #' #' # Count co-resistance between amoxicillin/clav acid and gentamicin, #' # so we can see that combination therapy does a lot more than mono therapy. #' # Please mind that `susceptibility()` calculates percentages right away instead. #' example_isolates %>% count_susceptible(AMC) # 1433 #' example_isolates %>% count_all(AMC) # 1879 #' #' example_isolates %>% count_susceptible(GEN) # 1399 #' example_isolates %>% count_all(GEN) # 1855 #' #' example_isolates %>% count_susceptible(AMC, GEN) # 1764 #' example_isolates %>% count_all(AMC, GEN) # 1936 #' #' # Get number of S+I vs. R immediately of selected columns #' example_isolates %>% #' select(AMX, CIP) %>% #' count_df(translate = FALSE) #' #' # It also supports grouping variables #' example_isolates %>% #' select(hospital_id, AMX, CIP) %>% #' group_by(hospital_id) %>% #' count_df(translate = FALSE) #' } #' } count_resistant <- function(..., only_all_tested = FALSE) { tryCatch( rsi_calc(..., ab_result = "R", only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export count_susceptible <- function(..., only_all_tested = FALSE) { tryCatch( rsi_calc(..., ab_result = c("S", "I"), only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export count_R <- function(..., only_all_tested = FALSE) { tryCatch( rsi_calc(..., ab_result = "R", only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export count_IR <- function(..., only_all_tested = FALSE) { if (message_not_thrown_before("count_IR", entire_session = TRUE)) { message_("Using `count_IR()` is discouraged; use `count_resistant()` instead to not consider \"I\" being resistant. This note will be shown once for this session.", as_note = FALSE) remember_thrown_message("count_IR") } tryCatch( rsi_calc(..., ab_result = c("I", "R"), only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export count_I <- function(..., only_all_tested = FALSE) { tryCatch( rsi_calc(..., ab_result = "I", only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export count_SI <- function(..., only_all_tested = FALSE) { tryCatch( rsi_calc(..., ab_result = c("S", "I"), only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export count_S <- function(..., only_all_tested = FALSE) { if (message_not_thrown_before("count_S", entire_session = TRUE)) { message_("Using `count_S()` is discouraged; use `count_susceptible()` instead to also consider \"I\" being susceptible. This note will be shown once for this session.", as_note = FALSE) remember_thrown_message("count_S") } tryCatch( rsi_calc(..., ab_result = "S", only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export count_all <- function(..., only_all_tested = FALSE) { tryCatch( rsi_calc(..., ab_result = c("S", "I", "R"), only_all_tested = only_all_tested, only_count = TRUE), error = function(e) stop_(e$message, call = -5)) } #' @rdname count #' @export n_rsi <- count_all #' @rdname count #' @export count_df <- function(data, translate_ab = "name", language = get_locale(), combine_SI = TRUE, combine_IR = FALSE) { tryCatch( rsi_calc_df(type = "count", data = data, translate_ab = translate_ab, language = language, combine_SI = combine_SI, combine_IR = combine_IR, combine_SI_missing = missing(combine_SI)), error = function(e) stop_(e$message, call = -5)) }